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首页> 外文期刊>Wireless personal communications: An Internaional Journal >Wavelet and Total Variation Based Method Using Adaptive Regularization for Speckle Noise Reduction in Ultrasound Images
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Wavelet and Total Variation Based Method Using Adaptive Regularization for Speckle Noise Reduction in Ultrasound Images

机译：基于小波和总变化的方法，使用自适应正则化对超声图像的散斑降噪

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摘要

Ultrasound (US) images are useful in medical diagnosis. US is preferred over other medical diagnosis technique because it is non-invasive in nature and has low cost. The presence of speckle noise in US images degrades its usefulness. A method that reduces the speckle noise in US images can help in correct diagnosis. This method also should preserve the important structural information in US images while removing the speckle noise. In this paper, a method for removing speckle noise using a combination of wavelet, total variation (TV) and morphological operations has been proposed. The proposed method achieves denoising by combining the advantages of the wavelet, TV and morphological operations along with the utilization of adaptive regularization parameter which controls the amount of smoothing during denoising. The work in this paper has the capability of reducing speckle noise while preserving the structural information in the denoised image. The proposed method demonstrates strong denoising for synthetic and real ultrasound images, which is also supported by the results of various quantitative measures and visual inspection.
机译：超声（美国）图像可用于医学诊断。美国在其他医学诊断技术中是优选的，因为它在自然界中是非侵入性的，并且成本低。美国图像中的斑点噪声的存在降低了其有用性。减少美国图像中斑点噪声的方法可以帮助正确诊断。此方法还应在消除斑点噪声的同时保留美国图像中的重要结构信息。本文已经提出了一种使用小波，总变化（TV）和形态操作的组合去除散斑噪声的方法。所提出的方法通过将小波，电视和形态学操作的优点与自适应正则化参数的利用相结合来实现去噪，该参数控制在去噪期间平滑量的平滑量。本文的工作具有减少散斑噪声的能力，同时保留在去噪图像中的结构信息。所提出的方法表明了合成和实际超声图像的强大去噪，其也得到了各种定量测量和目视检查的结果。

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